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YouTube Dubbing MCP

YouTube Dubbing MCP

by RTY2345RR
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

dubbing_extract_voice_samples

Idempotent

Extracts clean 4–14 second voice samples and transcripts per speaker, optionally sharing them after consent so a voice engine can clone voices and set speakers automatically; otherwise samples stay local.

Instructions

Cut a clean 4-14 second voice sample for each speaker from the source audio, with its transcript. With share=true each sample is uploaded to a temporary public file host (uguu.se, deleted after a few hours) so the voice engine can clone it, and the speaker's voice is set automatically. Ask the user before sharing someone's voice. With share=false the samples stay local.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>"
    },
    "name": "dubbing_extract_voice_samples"
  }
}

Input Schema

NameRequiredDescriptionDefault
shareNo
speakersNo
project_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the annotations: names the external host (uguu.se), discloses retention ('deleted after a few hours'), explains the data-leaves-machine consequence, and states that the speaker's voice is set automatically as a side effect. The openWorldHint annotation only signals external access generically; the description supplies the actual privacy and side-effect detail an agent needs before calling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and duration constraint, then the share-mode branch and consent warning in the order an agent needs them. Four sentences with minimal waste; 'so the voice engine can clone it' is slightly redundant but justifies the upload behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described, and the risky external-upload behavior plus the consent requirement are covered. The only real gap is the unexplained `speakers` parameter semantics for a tool whose per-speaker scope is central to its purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the load. It fully explains the meaning and consequences of `share` (upload vs local, auto voice-setting), but says nothing about the `speakers` array — whether it filters which speakers get samples or names them explicitly — and project_id is only implied by 'source audio'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Cut a clean 4-14 second voice sample for each speaker from the source audio, with its transcript'), including the output shape (sample + transcript) and the 4-14 second constraint. This is clearly distinguishable from sibling tools like dubbing_set_voice or dubbing_get_segments.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly branches on the share flag: share=true uploads samples and auto-sets the speaker's voice, share=false keeps samples local, plus a consent instruction ('Ask the user before sharing someone's voice'). What's missing is an explicit statement of when this tool should be chosen over alternatives such as dubbing_set_voice, though the auto-set behavior implies the relationship.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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